This document outlines a framework to build and enhance medical concept maps about obesity using text mining. The goals are to improve understanding of concept complexity in healthcare and assist medical professionals. So far, the researcher has reviewed literature, designed their methodology, extracted single terms using automated term recognition, and designed patterns to extract concepts, relationships, and other information. Future work includes identifying terms, analyzing existing concept maps, classifying and clustering terms, integrating results, validating the updated concept map, and exploring concept complexity in obesity.
Data Visuallization for Decision Making - Intel White PaperNicholas Tenhue
Visualization tools could help healthcare providers make sense of large volumes of complex health data and improve the speed and accuracy of decisions. This Intel White Paper is based on Nicholas Tenhue's MSc ICT Innovation thesis work.
Nicholas can be reached at http://www.nicholastenhue.com
Presentation about new indicators for innovation missions focusing on the mission to transform the prevention, diagnosis and treatment of AI, given at the EMAEE conference, University of Sussex 5 June 2019.
52 NURSERESEARCHER 2011, 18, 2issues in researchQualit.docxalinainglis
52 NURSERESEARCHER 2011, 18, 2
issues in research
Qualitative data analysis: the
framework approach
Introduction
The framework approach was developed in the 1980s by social policy research-
ers at the National Centre for Social Research as a method to manage and
analyse qualitative data in applied policy research. In this context, the research
brief is commissioned; aims and objectives are highly focused and the research-
ers work with structured topic guides to elicit and manage data. This approach
contrasts with entirely inductive approaches, such as grounded theory, where the
research is an iterative process and develops in response to the data obtained
and ongoing analysis. More recently, the framework approach has been gaining
in popularity as a means of analysing qualitative data derived from healthcare
research because it can be used to manage qualitative data and undertake
Abstract
Qualitative methods are invaluable for exploring the complexities of health
care and patient experiences in particular. Diverse qualitative methods are
available that incorporate different ontological and epistemological
perspectives. One method of data management that is gaining in popularity
among healthcare researchers is the framework approach. We will outline
this approach, discuss its relative merits and provide a working example of
its application to data management and analysis.
Authors
Joanna Smith MSc, BSc(Hons) RSCN, RGN is lecturer in children
and young people’s nursing, School of Nursing and Midwifery,
University of Salford, UK
Jill Firth RGN, PhD is a senior research fellow at the School of
Healthcare, University of Leeds, UK
Keywords
Qualitative research, framework approach, patient experiences
NURSERESEARCHER 2011, 18, 2 53
analysis systematically. This enables the researcher to explore data in depth
while simultaneously maintaining an effective and transparent audit trail, which
enhances the rigour of the analytical processes and the credibility of the findings
(Ritchie and Lewis 2003). This article will provide an overview of the framework
approach as a means of managing and analysing qualitative data. To illustrate its
application, we will draw on a study undertaken by one of the authors (JS) as
part of her programme of doctoral research investigating parents’ management
of their children’s hydrocephalus and shunt.
Context
Delivering health care that is responsive to individual needs is an integral part
of the modernisation agenda of the UK’s NHS. Policy directives for people with
long-term conditions emphasise actively involving patients in the management of
their conditions, valuing their expertise and working collaboratively with patients
(Department of Health (DH) 2001, 2005, 2007). When the patient is a child, this
includes understanding the views and experiences of their parents. The potential
benefits of this involvement include: empowering patients.
Massey University PhD Induction July 2018 NCTL SessionMartin McMorrow
These slides were prepared for a session from the National Centre for Teaching and Learning during the induction for new PhD students at Massey University New Zealand in July 2018.
Presentation carried out during the EMBC'16 conference in Orlando the 17th of August by Paulo Carvalho and Vicente Traver introducing the LINK project and the results of the first iteration with experts about the future opportunities and challenges for research on personalised health care for cardiovascular disease management.
PhD Thesis Defence: From Participation Factors to Co-Calibration of Patient- ...Vlad Manea
From Participation Factors to Co-Calibration of Patient- and Wearable-Reported Outcomes in Behavioural, Health, and Quality of Life Studies / PhD Thesis Defence • April 14th, 2021 • University of Copenhagen
Cite this work: From Participation Factors to Co-Calibration of Patient- and Wearable-Reported Outcomes in Behavioural, Health, and Quality of Life Studies. Vlad Manea. PhD thesis, Quality of Life Technologies Lab, Section of Human-Centered Computing, Department of Computer Science, Faculty of Science, University of Copenhagen, 2020. Copenhagen, Denmark
Abstract
Chronic diseases represent a significant share of the burden of disease globally. They are responsible for 86% of premature deaths in Europe. Unhealthy behaviours, such as physical inactivity, insufficient sleep, poor nutrition, and tobacco intake, explain up to 50% of chronic disease risk. However, the evidence is not precise enough to assess the risk for each disease. Human subject studies monitoring behaviours over long periods (longitudinally) during daily life (in situ) by leveraging unobtrusive (observational) technology can allow human behaviours to unfold. They can not only qualify, but also quantify the relationships between behaviours, health, and Quality of Life (QoL) outcomes from compliant participants.
This PhD thesis explores two research areas. In the first area, we research the motivation and facilitation of participation in human subject studies. We propose a presentational model using personalised stories to improve human studies’ participation. We design two unifying frameworks for conducting a wide range of human subject studies (mQoL mobile app, mQoL-Chat chatbot). They leverage two modules designed and developed by the author in mQoL-Lab, the lab platform of the Quality of Life Technologies lab.
In the second area, we research the relationships between behavioural, health, and QoL outcomes (co-calibration). We present the coQoL computational model for co-calibration. We demonstrate its feasibility in a study on N = 42 healthy older individuals (a population at risk, appropriate for disease prevention, and having benefitted from insufficient co-calibrations). They answered questionnaires on eight physical and psychological validated scales (physical activity: IPAQ, social support:
MSPSS, anxiety and depression: GADS, nutrition: PREDIMED and SelfMNA, memory: MFE, sleep: PSQI, and health-related QoL: EQ-5D-3L). They wore consumer wearables (Fitbit Charge 2) for up to two years. The wearables reported behavioural markers (physical activity, sleep, heart rate) in situ. We observed new relationships between these outcomes. We described the study’s human factors and data quality.
The scientific contributions in both research areas can inform the design of future studies leveraging consumer technology that monitors behaviours longitudinally in situ to assess and improve health and QoL.
“AN EVALUATION OF THE MANAGEMENT INFORMATION SYSTEM AND TECHNOLOGY IN HOSPITALS”
(GESITI/HOSPITALS).
UPDATED: NOVEMBER 18, 2011.
Abstract.
The Center for Information Technology Renato Archer (CTI), located at Campinas/SP/Br, is a unit of the Ministry of Science and Technology (MCT) and, is coordinating a research project involving several universities, from Brazil and abroad. The research project “Management of System and Information Technology in Hospitals” (GESITI/Hospitals) has the purpose of mapping out the management of Information Systems (IS) and Information Technology (IT) in hospitals, in order to identify their needs and demands, prospecting for unfolding, perform publication and, mainly, generate a Integrated Research Report (IRR) with a focus on, also, a Report Research Roadmap (RRR). This IRR/RRR is for open for free access, and should be used as decision making support by public and/or private managers.
Currently the research is being carried out by nineteen universities: sixteen Brazilian, one Mexican, one Argentina and one Portuguese. An important initial result of this research work, which makes use of the Interpretative (or Introspective) Methodology, has been the generation in Brazil of an unprecedented database regarding hospital management and, from which several important information is extracted. From each local information, obtained via Local Research Reports (LRR) where the research has been carried out (each local includes the average of results obtained in five (5) hospitals); it becomes possible to undertake local decision making. However, the main purpose of the project is the preparation, based on the integration of all LRR, of an IRR/RRR for national decision-making support.
For a better decision-making on issues of interest to managers regarding the better efficiency and effectiveness of hospital management, public and/or private, the IRR/RRR will also present an integrated comparative analyzes based on all LRR (from Brazil & Abroad).
Although it has not been directly mentioned, the final result, ultimate, from the research should be a significant improvement on the hospital management and on the decision-making process. These results must reflect on peoples more satisfied regarding a better health care.
This is a win-win project, since it is good for Brazil and good for all countries involved. The goal is to reach about one hundred (100) universities (local coordinators) involved.
Deep learning in healthcare: Oppotunities and challenges with Electronic Medi...Thien Q. Tran
Interested in deep learning for healthcare has grown strongly recent years besides with the successes in other domains such as Computer Vision, Natural Language Processing, Speech Recognition and so forth. This talk will try to give a brief look into the recent effort of research in deep learning for healthcare. Especially, this talk focuses on the opportunities and challenges in using electronic health records (EHR) data, which is one of the most important data sources in healthcare domain.
Identifying Structures in Social Conversations in NSCLC Patients through the ...IJERA Editor
The exploration of social conversations for addressing patient’s needs is an important analytical task in which
many scholarly publications are contributing to fill the knowledge gap in this area. The main difficulty remains
the inability to turn such contributions into pragmatic processes the pharmaceutical industry can leverage in
order to generate insight from social media data, which can be considered as one of the most challenging source
of information available today due to its sheer volume and noise. This study is based on the work by Scott
Spangler and Jeffrey Kreulen and applies it to identify structure in social media through the extraction of a
topical taxonomy able to capture the latent knowledge in social conversations in health-related sites. The
mechanism for automatically identifying and generating a taxonomy from social conversations is developed and
pressured tested using public data from media sites focused on the needs of cancer patients and their families.
Moreover, a novel method for generating the category’s label and the determination of an optimal number of
categories is presented which extends Scott and Jeffrey’s research in a meaningful way. We assume the reader is
familiar with taxonomies, what they are and how they are used.
Identifying Structures in Social Conversations in NSCLC Patients through the ...IJERA Editor
The exploration of social conversations for addressing patient’s needs is an important analytical task in which
many scholarly publications are contributing to fill the knowledge gap in this area. The main difficulty remains
the inability to turn such contributions into pragmatic processes the pharmaceutical industry can leverage in
order to generate insight from social media data, which can be considered as one of the most challenging source
of information available today due to its sheer volume and noise. This study is based on the work by Scott
Spangler and Jeffrey Kreulen and applies it to identify structure in social media through the extraction of a
topical taxonomy able to capture the latent knowledge in social conversations in health-related sites. The
mechanism for automatically identifying and generating a taxonomy from social conversations is developed and
pressured tested using public data from media sites focused on the needs of cancer patients and their families.
Moreover, a novel method for generating the category’s label and the determination of an optimal number of
categories is presented which extends Scott and Jeffrey’s research in a meaningful way. We assume the reader is
familiar with taxonomies, what they are and how they are used.
Case Retrieval using Bhattacharya Coefficient with Particle Swarm Optimizationrahulmonikasharma
Now a day, health information management and utilization is the demanding task to health informaticians for delivering the eminence healthcare services. Extracting the similar cases from the case database can aid the doctors to recognize the same kind of patients and their treatment details. Accordingly, this paper introduces the method called H-BCF for retrieving the similar cases from the case database. Initially, the patient’s case database is constructed with details of different patients and their treatment details. If the new patient comes for treatment, then the doctor collects the information about that patient and sends the query to the H-BCF. The H-BCF system matches the input query with the patient’s case database and retrieves the similar cases. Here, the PSO algorithm is used with the BCF for retrieving the most similar cases from the patient’s case database. Finally, the Doctor gives treatment to the new patient based on the retrieved cases. The performance of the proposed method is analyzed with the existing methods, such as PESM, FBSO-neural network, and Hybrid model for the performance measures accuracy and F-Measure. The experimental results show that the proposed method attains the higher accuracy of 99.5% and the maximum F-Measure of 99% when compared to the existing methods.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Data Visuallization for Decision Making - Intel White PaperNicholas Tenhue
Visualization tools could help healthcare providers make sense of large volumes of complex health data and improve the speed and accuracy of decisions. This Intel White Paper is based on Nicholas Tenhue's MSc ICT Innovation thesis work.
Nicholas can be reached at http://www.nicholastenhue.com
Presentation about new indicators for innovation missions focusing on the mission to transform the prevention, diagnosis and treatment of AI, given at the EMAEE conference, University of Sussex 5 June 2019.
52 NURSERESEARCHER 2011, 18, 2issues in researchQualit.docxalinainglis
52 NURSERESEARCHER 2011, 18, 2
issues in research
Qualitative data analysis: the
framework approach
Introduction
The framework approach was developed in the 1980s by social policy research-
ers at the National Centre for Social Research as a method to manage and
analyse qualitative data in applied policy research. In this context, the research
brief is commissioned; aims and objectives are highly focused and the research-
ers work with structured topic guides to elicit and manage data. This approach
contrasts with entirely inductive approaches, such as grounded theory, where the
research is an iterative process and develops in response to the data obtained
and ongoing analysis. More recently, the framework approach has been gaining
in popularity as a means of analysing qualitative data derived from healthcare
research because it can be used to manage qualitative data and undertake
Abstract
Qualitative methods are invaluable for exploring the complexities of health
care and patient experiences in particular. Diverse qualitative methods are
available that incorporate different ontological and epistemological
perspectives. One method of data management that is gaining in popularity
among healthcare researchers is the framework approach. We will outline
this approach, discuss its relative merits and provide a working example of
its application to data management and analysis.
Authors
Joanna Smith MSc, BSc(Hons) RSCN, RGN is lecturer in children
and young people’s nursing, School of Nursing and Midwifery,
University of Salford, UK
Jill Firth RGN, PhD is a senior research fellow at the School of
Healthcare, University of Leeds, UK
Keywords
Qualitative research, framework approach, patient experiences
NURSERESEARCHER 2011, 18, 2 53
analysis systematically. This enables the researcher to explore data in depth
while simultaneously maintaining an effective and transparent audit trail, which
enhances the rigour of the analytical processes and the credibility of the findings
(Ritchie and Lewis 2003). This article will provide an overview of the framework
approach as a means of managing and analysing qualitative data. To illustrate its
application, we will draw on a study undertaken by one of the authors (JS) as
part of her programme of doctoral research investigating parents’ management
of their children’s hydrocephalus and shunt.
Context
Delivering health care that is responsive to individual needs is an integral part
of the modernisation agenda of the UK’s NHS. Policy directives for people with
long-term conditions emphasise actively involving patients in the management of
their conditions, valuing their expertise and working collaboratively with patients
(Department of Health (DH) 2001, 2005, 2007). When the patient is a child, this
includes understanding the views and experiences of their parents. The potential
benefits of this involvement include: empowering patients.
Massey University PhD Induction July 2018 NCTL SessionMartin McMorrow
These slides were prepared for a session from the National Centre for Teaching and Learning during the induction for new PhD students at Massey University New Zealand in July 2018.
Presentation carried out during the EMBC'16 conference in Orlando the 17th of August by Paulo Carvalho and Vicente Traver introducing the LINK project and the results of the first iteration with experts about the future opportunities and challenges for research on personalised health care for cardiovascular disease management.
PhD Thesis Defence: From Participation Factors to Co-Calibration of Patient- ...Vlad Manea
From Participation Factors to Co-Calibration of Patient- and Wearable-Reported Outcomes in Behavioural, Health, and Quality of Life Studies / PhD Thesis Defence • April 14th, 2021 • University of Copenhagen
Cite this work: From Participation Factors to Co-Calibration of Patient- and Wearable-Reported Outcomes in Behavioural, Health, and Quality of Life Studies. Vlad Manea. PhD thesis, Quality of Life Technologies Lab, Section of Human-Centered Computing, Department of Computer Science, Faculty of Science, University of Copenhagen, 2020. Copenhagen, Denmark
Abstract
Chronic diseases represent a significant share of the burden of disease globally. They are responsible for 86% of premature deaths in Europe. Unhealthy behaviours, such as physical inactivity, insufficient sleep, poor nutrition, and tobacco intake, explain up to 50% of chronic disease risk. However, the evidence is not precise enough to assess the risk for each disease. Human subject studies monitoring behaviours over long periods (longitudinally) during daily life (in situ) by leveraging unobtrusive (observational) technology can allow human behaviours to unfold. They can not only qualify, but also quantify the relationships between behaviours, health, and Quality of Life (QoL) outcomes from compliant participants.
This PhD thesis explores two research areas. In the first area, we research the motivation and facilitation of participation in human subject studies. We propose a presentational model using personalised stories to improve human studies’ participation. We design two unifying frameworks for conducting a wide range of human subject studies (mQoL mobile app, mQoL-Chat chatbot). They leverage two modules designed and developed by the author in mQoL-Lab, the lab platform of the Quality of Life Technologies lab.
In the second area, we research the relationships between behavioural, health, and QoL outcomes (co-calibration). We present the coQoL computational model for co-calibration. We demonstrate its feasibility in a study on N = 42 healthy older individuals (a population at risk, appropriate for disease prevention, and having benefitted from insufficient co-calibrations). They answered questionnaires on eight physical and psychological validated scales (physical activity: IPAQ, social support:
MSPSS, anxiety and depression: GADS, nutrition: PREDIMED and SelfMNA, memory: MFE, sleep: PSQI, and health-related QoL: EQ-5D-3L). They wore consumer wearables (Fitbit Charge 2) for up to two years. The wearables reported behavioural markers (physical activity, sleep, heart rate) in situ. We observed new relationships between these outcomes. We described the study’s human factors and data quality.
The scientific contributions in both research areas can inform the design of future studies leveraging consumer technology that monitors behaviours longitudinally in situ to assess and improve health and QoL.
“AN EVALUATION OF THE MANAGEMENT INFORMATION SYSTEM AND TECHNOLOGY IN HOSPITALS”
(GESITI/HOSPITALS).
UPDATED: NOVEMBER 18, 2011.
Abstract.
The Center for Information Technology Renato Archer (CTI), located at Campinas/SP/Br, is a unit of the Ministry of Science and Technology (MCT) and, is coordinating a research project involving several universities, from Brazil and abroad. The research project “Management of System and Information Technology in Hospitals” (GESITI/Hospitals) has the purpose of mapping out the management of Information Systems (IS) and Information Technology (IT) in hospitals, in order to identify their needs and demands, prospecting for unfolding, perform publication and, mainly, generate a Integrated Research Report (IRR) with a focus on, also, a Report Research Roadmap (RRR). This IRR/RRR is for open for free access, and should be used as decision making support by public and/or private managers.
Currently the research is being carried out by nineteen universities: sixteen Brazilian, one Mexican, one Argentina and one Portuguese. An important initial result of this research work, which makes use of the Interpretative (or Introspective) Methodology, has been the generation in Brazil of an unprecedented database regarding hospital management and, from which several important information is extracted. From each local information, obtained via Local Research Reports (LRR) where the research has been carried out (each local includes the average of results obtained in five (5) hospitals); it becomes possible to undertake local decision making. However, the main purpose of the project is the preparation, based on the integration of all LRR, of an IRR/RRR for national decision-making support.
For a better decision-making on issues of interest to managers regarding the better efficiency and effectiveness of hospital management, public and/or private, the IRR/RRR will also present an integrated comparative analyzes based on all LRR (from Brazil & Abroad).
Although it has not been directly mentioned, the final result, ultimate, from the research should be a significant improvement on the hospital management and on the decision-making process. These results must reflect on peoples more satisfied regarding a better health care.
This is a win-win project, since it is good for Brazil and good for all countries involved. The goal is to reach about one hundred (100) universities (local coordinators) involved.
Deep learning in healthcare: Oppotunities and challenges with Electronic Medi...Thien Q. Tran
Interested in deep learning for healthcare has grown strongly recent years besides with the successes in other domains such as Computer Vision, Natural Language Processing, Speech Recognition and so forth. This talk will try to give a brief look into the recent effort of research in deep learning for healthcare. Especially, this talk focuses on the opportunities and challenges in using electronic health records (EHR) data, which is one of the most important data sources in healthcare domain.
Identifying Structures in Social Conversations in NSCLC Patients through the ...IJERA Editor
The exploration of social conversations for addressing patient’s needs is an important analytical task in which
many scholarly publications are contributing to fill the knowledge gap in this area. The main difficulty remains
the inability to turn such contributions into pragmatic processes the pharmaceutical industry can leverage in
order to generate insight from social media data, which can be considered as one of the most challenging source
of information available today due to its sheer volume and noise. This study is based on the work by Scott
Spangler and Jeffrey Kreulen and applies it to identify structure in social media through the extraction of a
topical taxonomy able to capture the latent knowledge in social conversations in health-related sites. The
mechanism for automatically identifying and generating a taxonomy from social conversations is developed and
pressured tested using public data from media sites focused on the needs of cancer patients and their families.
Moreover, a novel method for generating the category’s label and the determination of an optimal number of
categories is presented which extends Scott and Jeffrey’s research in a meaningful way. We assume the reader is
familiar with taxonomies, what they are and how they are used.
Identifying Structures in Social Conversations in NSCLC Patients through the ...IJERA Editor
The exploration of social conversations for addressing patient’s needs is an important analytical task in which
many scholarly publications are contributing to fill the knowledge gap in this area. The main difficulty remains
the inability to turn such contributions into pragmatic processes the pharmaceutical industry can leverage in
order to generate insight from social media data, which can be considered as one of the most challenging source
of information available today due to its sheer volume and noise. This study is based on the work by Scott
Spangler and Jeffrey Kreulen and applies it to identify structure in social media through the extraction of a
topical taxonomy able to capture the latent knowledge in social conversations in health-related sites. The
mechanism for automatically identifying and generating a taxonomy from social conversations is developed and
pressured tested using public data from media sites focused on the needs of cancer patients and their families.
Moreover, a novel method for generating the category’s label and the determination of an optimal number of
categories is presented which extends Scott and Jeffrey’s research in a meaningful way. We assume the reader is
familiar with taxonomies, what they are and how they are used.
Case Retrieval using Bhattacharya Coefficient with Particle Swarm Optimizationrahulmonikasharma
Now a day, health information management and utilization is the demanding task to health informaticians for delivering the eminence healthcare services. Extracting the similar cases from the case database can aid the doctors to recognize the same kind of patients and their treatment details. Accordingly, this paper introduces the method called H-BCF for retrieving the similar cases from the case database. Initially, the patient’s case database is constructed with details of different patients and their treatment details. If the new patient comes for treatment, then the doctor collects the information about that patient and sends the query to the H-BCF. The H-BCF system matches the input query with the patient’s case database and retrieves the similar cases. Here, the PSO algorithm is used with the BCF for retrieving the most similar cases from the patient’s case database. Finally, the Doctor gives treatment to the new patient based on the retrieved cases. The performance of the proposed method is analyzed with the existing methods, such as PESM, FBSO-neural network, and Hybrid model for the performance measures accuracy and F-Measure. The experimental results show that the proposed method attains the higher accuracy of 99.5% and the maximum F-Measure of 99% when compared to the existing methods.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
2. 2
Motivation
● Complex nature of obesity.
● Wide range of biomedical data sources available.
– implementation of biomedical text/data mining.
● Possible to reveal hidden links between obesity and other
diseases.
● Partial completed knowledge representation models of obesity.
● A systematic approach required for:
– analysis and interpretation of clinical knowledge.
3. 3
Concept Maps
● Knowledge representation models.
● Consisted of:
– nodes (concepts).
– links (relationships between the nodes).
● Aim: gather, understand, explore knowledge.
● Variety of users.
● No explicit detail.
● Implemented primarily in education.
5. 5
Aim
● To design a framework to build/enhance medical concept maps.
● To improve the understanding of health care concept
complexity.
● Assist medical professionals in the representation, exploration
and validation of their expert knowledge.
● Improvement of the clinical health care.
6. 6
Objectives
● Design and implement methods for health care concept
detection.
● Concept organisation in a concept map form.
● Method generation for concept map updates.
● Build a framework for the design/enhancement/validation of
medical concept maps.
● Methodology evaluation through the health problem of obesity:
– validation of obesity related concepts with current structured obesity
information available.
– identify gaps in clinical knowledge.
7. 7
Research Hypothesis &
Questions
-The analysis required to extract health care concepts.
-The approach to built and enhance a concept map.
-The concept map contribution in the representation/validation of knowledge.
-The text mining results help to understand/explore clinical problems.
Biomedical
Text Mining
Scientific
literature
Concept
map
Improvement of
health care
Framework
8. 8
Obesity
● Worldwide problem.
● Epidemic proportions:
– WHO rates (2005): 1.6 billion overweight, 400 million obese.
● Associations to various diseases.
● Complex risk factors and complications.
● Various aspects.
● Lots of research.
10. 10
Biomedical Text Mining
● Extraction of information from unstructured data of biomedical
nature.
● Discovery of new, previously unknown knowledge.
● Performed on documents with complex/specific terminology and
expressions.
● Challenges:
– language ambiguity.
– variation of language expression.
● Various tools and applications (Termine, Whatizit, GATE).
● Adaptation to user's tasks and requirements.
11. 11
What we are looking for?
● Risk Factors
● Causal Factors
● Confounding Factors
● Outcomes
● Complications
● Interventions
● ...
12. 12
Methodology Overview
1. Document retrieval.
2. Term/concept extraction.
3. Feature engineering and Information extraction:
- application of classification/clustering techniques.
4. Concept map design.
13. 13
Evaluation-Obesity Case Study
● Comparison:
– What ?
● biomedical text mining results.
● concept map information.
– How ?
● concepts and relationships.
● New ones.
● Examination/manipulation/validation of new knowledge by experts.
● Enhancement of the concept map.
14. 14
Progress so far (1)
● Corpus collection.
● Application of Automated Term Recognition (ATR).
● C-value method.
● Single word ATR:
– terminological head identification.
– word of a multi-word term that defines the term class.
– example:
● “Childhood diabetes type II”.
● Terminological head: “diabetes”.
15. 15
Progress so far (2)
● Ranking head measures:
– total head frequency,
– single head frequency,
– maximum and average C-value,
– abstract frequency,
– ratio of single head frequency/total head frequency,
– tf*idf (term frequency*inverse document frequency).
16. 16
Results
tf*idf total freq single freq abstract freq word freq max_c aver_c ratio
0
5
10
15
20
25
30
35
40
45
0
10
20
30
40
50
Statistical measure
Numberofkeywords
17. 17
Progress so far (3)
● Pattern extraction from abstracts for:
– risk, confounding and causal factors,
– interventions,
– complications,
– outcomes.
Obesity risk is increased among women with psychiatric disorders
Potential risk factor
19. 19
Future plan
Species identification in obesity corpus (Linneus)
Exploration of single word terms ATR
Calculation of z-score
Integration of single and multi-word terms
Lexical/semantic analysis of the existing concept map
Paper preparation for the extraction of single terms in text
Pattern extraction from manual analysis
Pattern rule design with Minor Third
Feature engineering
Clustering
Classification
Paper preparation for the classification of disease descriptors
Paper preparation for the clustering of health care concepts
Integration of the results
Preparation of the second year interview/report
Design of concept map relationships (exploration)
Application of visual mapping tools
Update of the new concept map
Comparison and validation of knowledge
Exploration of concept complexity in obesity
Paper preparation for the automatic design of clinical concept maps
Produced generic framework of the methodology
Writing the thesis
October 2010 April 2011 November 2011 May 2012
Year 3
Year 2
Date
Year 2 (1/2): Concept extraction
20. 20
Future plan
Species identification in obesity corpus (Linneus)
Exploration of single word terms ATR
Calculation of z-score
Integration of single and multi-word terms
Lexical/semantic analysis of the existing concept map
Paper preparation for the extraction of single terms in text
Pattern extraction from manual analysis
Pattern rule design with Minor Third
Feature engineering
Clustering
Classification
Paper preparation for the classification of disease descriptors
Paper preparation for the clustering of health care concepts
Integration of the results
Preparation of the second year interview/report
Design of concept map relationships (exploration)
Application of visual mapping tools
Update of the new concept map
Comparison and validation of knowledge
Exploration of concept complexity in obesity
Paper preparation for the automatic design of clinical concept maps
Produced generic framework of the methodology
Writing the thesis
October 2010 April 2011 November 2011 May 2012
Year 3
Year 2
Date
Year 2 (2/2): Concept structuring
21. 21
Future plan
Species identification in obesity corpus (Linneus)
Exploration of single word terms ATR
Calculation of z-score
Integration of single and multi-word terms
Lexical/semantic analysis of the existing concept map
Paper preparation for the extraction of single terms in text
Pattern extraction from manual analysis
Pattern rule design with Minor Third
Feature engineering
Clustering
Classification
Paper preparation for the classification of disease descriptors
Paper preparation for the clustering of health care concepts
Integration of the results
Preparation of the second year interview/report
Design of concept map relationships (exploration)
Application of visual mapping tools
Update of the new concept map
Comparison and validation of knowledge
Exploration of concept complexity in obesity
Paper preparation for the automatic design of clinical concept maps
Produced generic framework of the methodology
Writing the thesis
October 2010 April 2011 November 2011 May 2012
Year 3
Year 2
Date
Year 3: Design of the medical concept map
22. 22
Summary
● Framework creation for clinical concept map building and
enhancement.
● Improved understanding of health care concept complexity.
● So far:
– comprehension of literature review.
– methodology design.
– single ATR.
– pattern design.